The present invention relates generally to systems and methods for efficient handling of medical records via automated chart review processes. The present systems and methods enables more accurate and efficient identification of medical conditions, confirms the presence of documentation MEAT (Monitor, Evaluate, Assess and Treat), ensures human QA if effectively performed, minimizes auditing risk, and calculates costs/risks for patients.
Despite rapid growth of innovation in other fields in recent decades, the world of medical information, including patient medical records, billing, referrals, and a host of other information, has enjoyed little to no useful consolidation, reliability, or ease-of-access, leaving medical professionals, hospitals, clinics, and even insurance companies with many issues, such as unreliability of medical information, uncertainty of diagnosis, lack of standard, and a slew of other related problems.
One of the challenges facing those in the medical or related areas is that human intervention is required to perform medical chart reviews. Reviewing medical charts is a time consuming and labor intensive process, whereby trained individuals review the documents in order to ensure the documents are admissible, identify conditions found within the charts (for billing purposes), and ensuring other required information is present in the document in order to bill appropriately. One major aspect of this chart review process includes medical coding (also known as clinical coding, diagnostic coding or health care coding), accuracy assurance, identification of MEAT data within documents, and the like.
In order to ensure chart review is done accurately, redundancy of review is built into the manual systems currently employed. These redundancies further exacerbate the time and effort required for chart review. Moreover, despite these precautions, chart review is still often subject to erroneous or incomplete analysis.
It is therefore apparent that an urgent need exists for an efficient means for reviewing medical charts. Such systems and methods enable more efficient identification of admissible medical documents, condition classification, MEAT classification, and audit protection. Such systems and methods may also increase efficiency of human quality assurance steps, and risk analysis.